Information retrieval (IR) is the process of locating documents in a collection or from an unbounded set such as the Web based on an expression of a human user's information need. The user's information need is typically expressed in the form of a query which consists of a set of keywords and/or logical operators. A particular type of information retrieval is Question Answering (Q&A).
Unlike information retrieval, in Q&A the user expresses his or her information need in the form of a factual natural language question (e.g., “who played Don Vito Corleone in the movie ‘The Godfather’?”).
Unlike information retrieval, Q&A returns a short snippet or snippets of text (e.g., phrases) which provide the exact answer to the question rather than a document or set of documents related to the question.
Unlike information retrieval, Q&A systems must understand the user's questions to a deeper level, e.g., properly dealing with negations (“Not”) and/or the question's discourse, logical, or temporal structure (“Which U.S. president succeeded Nixon?”, “What is the smallest country in Europe?”) When given an input such as “What is the capital of India?”, an IR-based system will typically return documents about India and about capital (in all of its possible senses) but not necessarily documents which contain the answer “New Delhi”. Q&A systems will weed out the wrong senses of capital (e.g., “financial capital”) and concentrate on the meaning of that word (“head city”) that fits best the overall structure of the question.